MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 35-44
Nationality: United States
Marital status: Divorced 
First language: English 
Religion: Other, please specify. agnostic
Education: High school or below
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to rock/indie music;Use social media;Other (Please specify) Play Sims 4
Devices used daily: Laptop;Smartphone;Other Desktop
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Nearly every day
LLMs used: Meta Llama 2 
LLM use cases: Translation;Brainstorming;Writing (e.g., composing emails);Solving math or logical problems;Answering questions about general knowledge 
Contexts of LLM use: Work;Personal;Learning 
Prompt 1: how do I know the seal around my oven door is worn out
Prompt 2: how do you spell cumulative 
Prompt 3: when does Law and order criminal intent new season start
Prompt 4: what should I name my sourdough starter
Prompt 5: how many days supply in 3 Ozempic pens
Prompt 6: write me an email to my crush , make it flirty
Prompt 7: how to spell assess
Prompt 8: most efficient oil-filled radiator heater
Prompt 9: ounces to milileter conversion
Prompt 10: How old is Gordon Ramsay
Comments: no
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: Hispanic 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Student
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to jazz;Listen to rock/indie music;Listen to classical music;Listen to hiphop and rap;Go to gigs;Exercise;Use social media;Go to museums and galleries;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Other (specify) Resumes
Contexts of LLM use: Work;Personal 
Prompt 1: Best work
Prompt 2: Technical skills
Prompt 3: Language fluent
Prompt 4: School
Prompt 5: Experience
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Prefer not to say 
First language: English 
Religion: Nothing 
Education: Prefer not to say
Mother's education: Graduate degree
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): Prefer not to say
Home: Prefer not to say 
Employment: Self-employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Go to the opera 
Devices used daily: Smartphone;Laptop 
NLP tools known: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Other Deepseek
LLM use cases: Answering questions about general knowledge;Play games 
Contexts of LLM use: Personal 
Prompt 1: what is the secret to life?
Prompt 2: Where is all the money going?
Prompt 3: Will 2025 be the year of Positive Change for Humanty?
Prompt 4: How well Crypto do in 2024?
Prompt 5: What is Trump Coin
Prompt 6: what time is it in Russia?
Prompt 7: How far are we from Personal FLying Vehicles?
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Prefer not to say
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Exercise;Listen to classical music;Attend football matches;Watch sports 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Character.AI 
LLM use cases: Brainstorming;Solving math or logical problems;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Learning;School/University;Work 
Prompt 1: Crank and slider analysis
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Prefer not to say
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to jazz;Listen to rock/indie music;Listen to hiphop and rap;Watch sports;Do arts and crafts;Go to museums and galleries;Use social media 
Devices used daily: Smartphone;Laptop;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Collecting references;Answering questions about general knowledge 
Contexts of LLM use: Personal;Creative or artistic 
Prompt 1: what's the best back workout with dumbells for beginners?
Prompt 2: will not meeting the daily calorie requirement make losing weight harder?
Prompt 3: Could a person breath if they went back in time 95 million years ago?
Prompt 4: In Breaking Bad, How would things have played out differently if Jesse got away after killing Gale?
Prompt 5: How does Nikola Jokic generate such a high vorp?
Prompt 6: How does Aaron Judge accumulate so much WAR?
Gender: Male 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Doctorate or above
Mother's education: Doctorate or above
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Translation;Writing (e.g., composing emails);Solving math or logical problems 
Contexts of LLM use: Personal;Work 
Prompt 1: Creative brainstorming
Prompt 2: Data analysis and insights
Prompt 3: Problem-solving
Prompt 4: Learning and tutoring
Prompt 5: Personalized recommendations
Prompt 6: Automation of repetitive tasks
Prompt 7: Customer service:
Prompt 8: Creative brainstorming
Prompt 9: Data analysis and insights
Prompt 10: Problem-solving
Comments: No
Gender: Female 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Other (Please specify) Read
Devices used daily: Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
Frequency of LLM use: Nearly every day
LLMs used: Google Gemini;Snapchat My AI 
LLM use cases: Translation;Brainstorming;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Play games;Learning (e.g., explaining complex concepts in simple terms);Summarizing long texts 
Contexts of LLM use: Learning;Personal 
Prompt 1: Please check my grammar
Prompt 2: Please summarize 
Prompt 3: Proofread my paper
Prompt 4: How do I figure out this math problem
Prompt 5: What is the best sushi restaurant in town
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Listen to classical music;Exercise;Watch dance or ballet 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Bard;Pi 
LLM use cases: Translation;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Writing (e.g., composing emails) 
Contexts of LLM use: Personal;Work 
Prompt 1: WORK
Prompt 2: TRAINING
Prompt 3: EASY WRITTING
Prompt 4: GAMES
Prompt 5: SOCIAL MEDIA
Prompt 6: HOW TO RELAX
Prompt 7: WAYS TO AVOID ANGER
Prompt 8: BEST BOOKS TO READ ON HOW TO BE INDUSTRIOUS 
Prompt 9: HOW TO TALK IN PUBLIC
Prompt 10: HOW TO COMMUNICATE
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Stay-at-home spouse or partner
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Use social media;Exercise;Do arts and crafts 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Never
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Other, please specify. Spirtual
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Homemaker
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Exercise;Go to gigs;Use social media 
Devices used daily: Smartphone;Laptop 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Character.AI;Google Gemini 
LLM use cases: Brainstorming;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation 
Contexts of LLM use: Personal;Learning 
Prompt 1: How to mutually exchange social housing
Comments: I've recently started using Gemini and meta from Facebook chatbots
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Employed part time
Mother's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Use social media;Go to gigs;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Answering questions about general knowledge;Brainstorming;Solving math or logical problems 
Contexts of LLM use: Learning;Work 
Prompt 1: I have an old iPhone and a new one I want to transfer information from old to new what is the step by step process please
Prompt 2: n 2010, I took a break from my career to focus on raising my children. Now that they are in secondary school, I am eager to pursue a job with increased hours.
Prompt 3: Could I do an NVQ level 2 Pharmacy Dispensing assistant course in the UK if I currently don’t work in a pharmacy?
Prompt 4: Hello! How are you doing today? Just curious, what do you think about moldavite? It's quite an interesting stone—some people believe it has unique properties. What’s your take on 
Prompt 5: What possible problems to look out for with the body after menopause ends
Prompt 6: Whats 162cm in feet and inches
Prompt 7: What’s +44 mean on phone numbers
Prompt 8: How far away is 15 light years
Prompt 9: What’s Hanukkah
Prompt 10: I mean my daughter is 11 and a half years of age, How tall will she be at 16 years of age? If she is 5 foot now.
Comments: I renewed my chatbox subscription a couple of months ago and I asked it what year it was working in, it replied 2020 !
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Student
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Exercise;Do arts and crafts;Use social media;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone 
NLP tools known: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Completing assignments;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: School/University 
Prompt 1: 990, 1010, 1080, 1030, 1090, 1060, 1070, 1100, 1160, 1200 add them all up
Prompt 2: divide by 10
Prompt 3: differences from the mean
Prompt 4: averages of those squared differences
Prompt 5: square root of that
Prompt 6: what does this standard deviation show ?
Prompt 7: is this a low or high standard deviation
Prompt 8: this data is to do with annual rainfall in the uk
Prompt 9: its from this website https://www.metoffice.gov.uk/research/climate/maps-and-data/uk-temperature-rainfall-and-sunshine-time-series
Prompt 10: can you find me a link to a graph surrounding annual rainfall in the uk in the last 10 years?
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Use social media 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Never
Gender: Male 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Go to gigs;Listen to rock/indie music;Use social media;Exercise 
Devices used daily: Tablet;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming 
Contexts of LLM use: Entertainment;Learning;Personal 
Prompt 1: Does hypnotherapy cure depression?
Prompt 2: 100 creative ways to promote a new music single
Prompt 3: 30 content ideas for musicians on social media
Prompt 4: write me a story about Southsea market
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Jewish 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Exercise 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Generic chatbot conversation;Solving math or logical problems 
Contexts of LLM use: Learning;Personal 
Prompt 1: How many planets are there in milky way
Prompt 2: What is consciousness 
Prompt 3: How old is the earth 
Prompt 4: Who was Carl Sagan 
Prompt 5: How did the dinosaurs go extinct 
Prompt 6: What’s my name 
Prompt 7: Is there a god
Prompt 8: How many wars does the United States start 
Prompt 9: Who owns the most nuclear weapons 
Prompt 10: Will AI take over the world
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Prefer not to say 
Education: Prefer not to say
Mother's education: Prefer not to say
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 3
Home: Prefer not to say 
Employment: Prefer not to say
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Exercise;Use social media 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Never
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Self-employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to jazz;Listen to classical music;Listen to rock/indie music;Listen to hiphop and rap;Go to gigs;Exercise;Use social media;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Other (specify) In surveys
Contexts of LLM use: Work 
Comments: no
Gender: Male 
Age: 55-60
Nationality: United States
Ethnicity: Black or African American 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 1
Home: Other (Please specify) live with partner
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Prefer not to say
Hobbies: Listen to hiphop and rap;Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming 
Contexts of LLM use: Entertainment 
Prompt 1: How to drain my brake
Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Other (Please Specify) In a serious relationship (not living together)
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Watch sports 
Devices used daily: Smartphone;Other Desktop
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Translation;Brainstorming;Analyze data;Answering questions about general knowledge;Summarizing long texts 
Contexts of LLM use: Learning;Personal 
Prompt 1: How to format a specific address for another country
Prompt 2: What temperature to cook chicken in the air fryer
Prompt 3: Suggestions for what to season potatoes and chicken with using specific seasonings and spices that I have
Prompt 4: How to correctly Nasal Douche after a sinus surgery
Prompt 5: How to correctly calculate calorie intake for rice because the packaging was confusing
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: Google Gemini 
LLM use cases: Answering questions about general knowledge 
Contexts of LLM use: Entertainment
Gender: Male 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Self-employed part time
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Use social media;Other (Please specify) Solving Geometry-Olympiad Puzzles, and practicing elementary algebra skills to ensure and empower perfection
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Other (specify) Copilot
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: GitHub Copilot 
LLM use cases: Coding;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Solving math or logical problems;Answering questions about general knowledge 
Contexts of LLM use: Other (specify) have NOT used ChatGPT
Prompt 1: Solve mathematics-related questions
Comments: no